U.S. patent application number 17/643741 was filed with the patent office on 2022-03-31 for on-demand cloud robots for robotic process automation.
This patent application is currently assigned to UiPath, Inc.. The applicant listed for this patent is UiPath, Inc.. Invention is credited to Bo-Ying FU, Andrew HALL, Tarek MADKOUR.
Application Number | 20220100539 17/643741 |
Document ID | / |
Family ID | |
Filed Date | 2022-03-31 |
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United States Patent
Application |
20220100539 |
Kind Code |
A1 |
MADKOUR; Tarek ; et
al. |
March 31, 2022 |
ON-DEMAND CLOUD ROBOTS FOR ROBOTIC PROCESS AUTOMATION
Abstract
Systems and methods for implementing robotic process automation
(RPA) in the cloud are provided. An instruction for managing an RPA
robot is received at an orchestrator in a cloud computing
environment from a user in a local computing environment. In
response to receiving the instruction, the instruction for managing
the RPA robot is effectuated.
Inventors: |
MADKOUR; Tarek; (Sammamish,
WA) ; FU; Bo-Ying; (Edmonds, WA) ; HALL;
Andrew; (Charlottesville, VA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
UiPath, Inc. |
New York |
NY |
US |
|
|
Assignee: |
UiPath, Inc.
New York
NY
|
Appl. No.: |
17/643741 |
Filed: |
December 10, 2021 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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16725706 |
Dec 23, 2019 |
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17643741 |
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International
Class: |
G06F 9/451 20060101
G06F009/451; G06F 9/455 20060101 G06F009/455 |
Claims
1. A computer-implemented method comprising: receiving, at an
orchestrator in a cloud computing environment from a user in a
local computing environment, a command for executing a job for
performing a robotic process automation (RPA) workflow in the cloud
computing environment, the command comprising an instruction for
managing an RPA robot; in response to receiving the command for
executing the job, effectuating the instruction for managing the
RPA robot; performing a task by the RPA robot executing in the
cloud computing environment; and transmitting results of the task
from the RPA robot executing in the cloud computing environment to
the user in the local computing environment.
2. The computer-implemented method of claim 1, wherein the
instruction for managing the RPA robot comprises an instruction for
creating the RPA robot, the method further comprising: generating
an image of a virtual machine; and creating one or more new virtual
machines for executing the RPA robot on based on the image.
3. The computer-implemented method of claim 2, wherein the virtual
machine is configured by the user via remote desktop protocol.
4. The computer-implemented method of claim 2, wherein the virtual
machine is configured with a virtual private network to enable the
RPA robot to access data behind a firewall of a local network in
the local computing environment.
5. The computer-implemented method of claim 4, wherein creating one
or more new virtual machines for executing the RPA robot on based
on the image comprises: automatically creating the one or more new
virtual machines based on a workload.
6. The computer-implemented method of claim 1, wherein the RPA
robot is part of a robot pool, the method further comprising:
automatically updating RPA robots of the robot pool during a
maintenance window, wherein the RPA robots are automatically set to
not accept new jobs during the maintenance window.
7. The computer-implemented method of claim 6, wherein
automatically updating RPA robots of the robot pool during a
maintenance window comprises: during a first period of time of the
maintenance window, automatically updating a first portion of the
RPA robots of the robot pool while a second portion of the RPA
robots of the robot pool continues to accept jobs; and in response
to the updating of the first portion being completed, during a
second period of time of the maintenance window, automatically
updating the second portion of the RPA robots while the first
portion of the RPA robots accepts jobs.
8. A cloud computing environment comprising: a processor; a memory;
a cloud orchestrator executing in the cloud computing environment
for: receiving, from a user in a local computing environment, a
command for executing a job for performing a robotic process
automation (RPA) workflow in the cloud computing environment, the
command comprising an instruction for managing one or more RPA
robots, and in response to receiving the command for executing the
job, effectuating the instruction for managing the RPA robot; and a
cloud robot pool comprising the one or more RPA robots for:
performing a task in the cloud computing environment for the user
in the local computing environment, and transmitting results of the
task from the one or more RPA robots executing in the cloud
computing environment to the user in the local computing
environment.
9. The cloud computing environment of claim 8, wherein the
instruction for managing the one or more RPA robots comprises an
instruction for creating the one or more RPA robots, the cloud
orchestrator further for: generating an image of a virtual machine;
and creating one or more new virtual machines for executing the one
or more RPA robots on based on the image.
10. The cloud computing environment of claim 9, wherein the virtual
machine is configured by the user via remote desktop protocol.
11. The cloud computing environment of claim 9, wherein the virtual
machine is configured with a virtual private network to enable the
one or more RPA robots to access data behind a firewall of a local
network in the local computing environment.
12. The cloud computing environment of claim 11, wherein creating
one or more new virtual machines for executing the one or more RPA
robots on based on the image comprises: automatically creating the
one or more new virtual machines based on a workload.
13. The cloud computing environment of claim 8, the cloud
orchestrator further for: automatically updating the one or more
RPA robots of the cloud robot pool during a maintenance window,
wherein the one or more RPA robots are automatically set to not
accept new jobs during the maintenance window.
14. The cloud computing environment of claim 13, wherein
automatically updating the one or more RPA robots of the cloud
robot pool during a maintenance window comprises: during a first
period of time of the maintenance window, automatically updating a
first portion of the one or more RPA robots of the cloud robot pool
while a second portion of the one or more RPA robots of the cloud
robot pool continues to accept jobs; and in response to the
updating of the first portion being completed, during a second
period of time of the maintenance window, automatically updating
the second portion of the one or more RPA robots while the first
portion of the one or more RPA robots accepts jobs.
15. A computer-implemented method comprising: maintaining a cloud
robot pool comprising one or more robotic process automation (RPA)
robots in a cloud computing environment, the one or more RPA robots
performing a task in the cloud computing environment for a user in
a local computing environment and transmitting results of the task
from the one or more RPA robots executing in the cloud computing
environment to the user in the local computing environment; and
managing the cloud robot pool using a cloud orchestrator
implemented in the cloud computing environment, the cloud
orchestrator: receiving, from a user in a local computing
environment, a command for executing a job for performing an RPA
workflow in the cloud computing environment, the command comprising
an instruction for managing the one or more RPA robots, and in
response to receiving the command for executing the job,
effectuating the instruction for managing the one or more RPA
robots.
16. The computer-implemented method of claim 15, wherein the
instruction for managing the one or more RPA robots comprises an
instruction for creating one or more additional RPA robots, the
cloud orchestrator further: generating an image of a virtual
machine; and creating one or more new virtual machines for
executing the one or more additional RPA robots on based on the
image.
17. The computer-implemented method of claim 16, wherein the
virtual machine is configured by the user via remote desktop
protocol.
18. The computer-implemented method of claim 16, wherein the
virtual machine is configured with a virtual private network to
enable the one or more RPA robots to access data behind a firewall
of a local network in the local computing environment.
19. The computer-implemented method of claim 18, wherein creating
one or more new virtual machines for executing the one or more
additional RPA robots on based on the image comprises:
automatically creating the one or more new virtual machines based
on a workload.
20. The computer-implemented method of claim 15, the orchestrator
further: automatically updating the one or more RPA robots of the
cloud robot pool during a maintenance window, wherein the one or
more RPA robots are automatically set to not accept new jobs during
the maintenance window.
21. The computer-implemented method of claim 20, wherein
automatically updating the one or more RPA robots of the cloud
robot pool during a maintenance window comprises: during a first
period of time of the maintenance window, automatically updating a
first portion of the one or more RPA robots of the cloud robot pool
while a second portion of the one or more RPA robots of the cloud
robot pool continues to accept jobs; and in response to the
updating of the first portion being completed, during a second
period of time of the maintenance window, automatically updating
the second portion of the one or more RPA robots while the first
portion of the one or more RPA robots accepts jobs.
Description
[0001] This application is a continuation-in-part of U.S. patent
application Ser. No. 16/725,706, filed Dec. 23, 2019, the
disclosure of which is incorporated herein by reference in its
entirety.
TECHNICAL FIELD
[0002] The present invention relates generally to robotic process
automation, and more particularly to on-demand cloud robots for
robotic process automation.
BACKGROUND
[0003] Robotic process automation (RPA) is a form of process
automation that uses software robots to automate workflows.
Typically, RPA is implemented for an enterprise on a local
computing infrastructure that is managed by the enterprise.
However, such local implementation of RPA requires the maintenance
of a large computing infrastructure for provisioning servers that
are continuously running. Recently, cloud computing technology has
been leveraged to implement robots in the cloud. However, the cost
of maintaining continuously running robots which are idle is highly
inefficient.
BRIEF SUMMARY OF THE INVENTION
[0004] In accordance with one or more embodiments, systems and
methods for cloud-based management of robotic process automation
(RPA) robots are provided. A command for executing a job for
performing an RPA workflow in a cloud computing environment is
received at an orchestrator in the cloud computing environment from
a user in a local computing environment. The command comprises an
instruction for managing an RPA robot. The instruction may include
an instruction for creating the RPA robot, provisioning the RPA
robot, or scheduling a task on the RPA robot. In response to
receiving the command for executing the job, the instruction for
managing the RPA robot is effectuated. A task is performed by the
RPA robot executing in the cloud computing environment and results
of the task is transmitted from the RPA robot executing in the
cloud computing environment to the user in the local computing
environment.
[0005] In one embodiment, where the instruction for managing the
RPA robot is an instruction for creating the RPA robot, an image of
a virtual machine is generated and one or more new virtual machines
for executing the RPA robot on are created based on the image. The
virtual machine may be configured by the user via remote desktop
protocol. The virtual machine may be configured with a virtual
private network to enable the RPA robot to access data behind a
firewall of a local network in the local computing environment. The
one or more new virtual machines may be automatically created based
on a workload.
[0006] In one embodiment, where the RPA robot is part of a robot
pool, RPA robots of the robot pool may be automatically updated
during a maintenance window, wherein the RPA robots are
automatically set to not accept new jobs during the maintenance
window. In one embodiment, during a first period of time of the
maintenance window, a first portion of the RPA robots of the robot
pool is automatically updated while a second portion of the RPA
robots of the robot pool continues to accept jobs. In response to
the updating of the first portion being complete, during a second
period of time of the maintenance window, the second portion of the
RPA robots is automatically updated while the first portion of the
one or more RPA robots accepts jobs.
[0007] In accordance with one embodiment, a cloud computing
environment comprising a processor and memory is provided. The
cloud computing environment comprises a cloud orchestrator
executing in the cloud computing environment and a cloud robot pool
comprising one or more RPA robots. The cloud orchestrator is for
receiving, from a user in a local computing environment, a command
for executing a job for performing a robotic process automation
(RPA) workflow in the cloud computing environment. The command
comprises an instruction for managing one or more RPA robots. In
response to receiving the command for executing the job, the
instruction for managing the RPA robot is effectuated. The one or
more RPA robots are for performing a task in the cloud computing
environment for the user in the local computing environment and
transmitting results of the task from the one or more RPA robots
executing in the cloud computing environment to the user in the
local computing environment.
[0008] In accordance with one embodiment, systems and methods for
cloud-based management of robotic process automation (RPA) robots
are provided. A cloud robot pool comprising one or more robotic
process automation (RPA) robots in a cloud computing environment is
maintained. The one or more RPA robots perform a task in the cloud
computing environment for a user in the local computing environment
and transmit results of the task from the one or more RPA robots
executing in the cloud computing environment to the user in the
local computing environment. The cloud robot pool is managed using
a cloud orchestrator implemented in the cloud computing
environment. The cloud orchestrator receives, from a user in a
local computing environment, a command for executing a job for
performing an RPA workflow in the cloud computing environment. The
command comprises an instruction for managing the one or more RPA
robots. In response to receiving the command for executing the job,
the instruction for managing the one or more RPA robots is
effectuated.
[0009] These and other advantages of the invention will be apparent
to those of ordinary skill in the art by reference to the following
detailed description and the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0010] FIG. 1 is an architectural diagram illustrating a robotic
process automation system, according to an embodiment of the
invention;
[0011] FIG. 2 is an architectural diagram illustrating an example
of a deployed robotic process automation system, according to an
embodiment of the invention;
[0012] FIG. 3 is an architectural diagram illustrating a simplified
deployment example of a robotic process automation system,
according to an embodiment of the invention;
[0013] FIG. 4 shows a network architecture for implementing
cloud-based management of robotic process automation robots,
according to an embodiment of the invention;
[0014] FIG. 5 shows a method for cloud-based management of robotic
process automation robots, according to an embodiment of the
invention;
[0015] FIG. 6 is a block diagram of a computing system according to
an embodiment of the invention;
[0016] FIG. 7 shows a user interface of a cloud orchestrator, in
accordance with one or more embodiments;
[0017] FIG. 8 shows a dialog box for defining properties of a
generated snapshot image, in accordance with one or more
embodiments; and
[0018] FIG. 9 shows another user interface of a cloud orchestrator,
in accordance with one or more embodiments.
DETAILED DESCRIPTION
[0019] Robotic process automation (RPA) is used for automating
various tasks and workflows. FIG. 1 is an architectural diagram of
an RPA system 100, in accordance with one or more embodiments. As
shown in FIG. 1, RPA system 100 includes a designer 102 to allow a
developer to design automation processes using workflows. More
specifically, designer 102 facilitates the development and
deployment of workflows and robots for performing activities in the
workflows. Designer 102 may provide a solution for application
integration, as well as automating third-party applications,
administrative Information Technology (IT) tasks, and business
processes for contact center operations. One commercial example of
an embodiment of designer 102 is UiPath Studio.TM..
[0020] In designing the automation of rule-based processes, the
developer controls the execution order and the relationship between
a custom set of steps developed in a workflow, defined herein as
"activities." Each activity may include an action, such as clicking
a button, reading a file, writing to a log panel, etc. In some
embodiments, workflows may be nested or embedded.
[0021] Some types of workflows may include, but are not limited to,
sequences, flowcharts, Finite State Machines (FSMs), and/or global
exception handlers. Sequences may be particularly suitable for
linear processes, enabling flow from one activity to another
without cluttering a workflow. Flowcharts may be particularly
suitable to more complex business logic, enabling integration of
decisions and connection of activities in a more diverse manner
through multiple branching logic operators. FSMs may be
particularly suitable for large workflows. FSMs may use a finite
number of states in their execution, which are triggered by a
condition (i.e., transition) or an activity. Global exception
handlers may be particularly suitable for determining workflow
behavior when encountering an execution error and for debugging
processes.
[0022] Once a workflow is developed in designer 102, execution of
business processes is orchestrated by a conductor 104, which
orchestrates one or more robots 106 that execute the workflows
developed in designer 102. One commercial example of an embodiment
of conductor 104 is UiPath Orchestrator.TM.. Conductor 220
facilitates management of the creation, monitoring, and deployment
of resources in an RPA environment. In one example, conductor 104
is a web application. Conductor 104 may also function as an
integration point with third-party solutions and applications.
[0023] Conductor 104 may manage a fleet of robots 106 by connecting
and executing robots 106 from a centralized point. Conductor 104
may have various capabilities including, but not limited to,
provisioning, deployment, configuration, queueing, monitoring,
logging, and/or providing interconnectivity. Provisioning may
include creation and maintenance of connections between robots 106
and conductor 104 (e.g., a web application). Deployment may include
assuring the correct delivery of package versions to assigned
robots 106 for execution. Configuration may include maintenance and
delivery of robot environments and process configurations. Queueing
may include providing management of queues and queue items.
Monitoring may include keeping track of robot identification data
and maintaining user permissions. Logging may include storing and
indexing logs to a database (e.g., an SQL database) and/or another
storage mechanism (e.g., ElasticSearch.RTM., which provides the
ability to store and quickly query large datasets). Conductor 104
may provide interconnectivity by acting as the centralized point of
communication for third-party solutions and/or applications.
[0024] Robots 106 are execution agents that run workflows built in
designer 102. One commercial example of some embodiments of robots
106 is UiPath Robots.TM.. Types of robots 106 may include, but are
not limited to, attended robots 108 and unattended robots 110.
Attended robots 108 are triggered by a user or user events and
operate alongside a human user on the same computing system.
Attended robots 108 may help the human user accomplish various
tasks, and may be triggered directly by the human user and/or by
user events. In the case of attended robots, conductor 104 may
provide centralized process deployment and a logging medium. In
certain embodiments, attended robots 108 can only be started from a
"robot tray" or from a command prompt in a web application.
Unattended robots 110 operate in an unattended mode in virtual
environments and can be used for automating many processes, e.g.,
for high-volume, back-end processes and so on. Unattended robots
110 may be responsible for remote execution, monitoring,
scheduling, and providing support for work queues. Both attended
and unattended robots may automate various systems and applications
including, but not limited to, mainframes, web applications, VMs,
enterprise applications (e.g., those produced by SAP.RTM.,
SalesForce.RTM., Oracle.RTM., etc.), and computing system
applications (e.g., desktop and laptop applications, mobile device
applications, wearable computer applications, etc.).
[0025] In some embodiments, robots 106 install the Microsoft
Windows.RTM. Service Control Manager (SCM)-managed service by
default. As a result, such robots 106 can open interactive
Windows.RTM. sessions under the local system account, and have the
rights of a Windows.RTM. service. In some embodiments, robots 106
can be installed in a user mode with the same rights as the user
under which a given robot 106 has been installed.
[0026] Robots 106 in some embodiments are split into several
components, each being dedicated to a particular task. Robot
components in some embodiments include, but are not limited to,
SCM-managed robot services, user mode robot services, executors,
agents, and command line. SCM-managed robot services manage and
monitor Windows.RTM. sessions and act as a proxy between conductor
104 and the execution hosts (i.e., the computing systems on which
robots 106 are executed). These services are trusted with and
manage the credentials for robots 106. A console application is
launched by the SCM under the local system. User mode robot
services in some embodiments manage and monitor Windows.RTM.
sessions and act as a proxy between conductor 104 and the execution
hosts. User mode robot services may be trusted with and manage the
credentials for robots 106. A Windows.RTM. application may
automatically be launched if the SCM-managed robot service is not
installed. Executors may run given jobs under a Windows.RTM.
session (e.g., they may execute workflows) and they may be aware of
per-monitor dots per inch (DPI) settings. Agents may be
Windows.RTM. Presentation Foundation (WPF) applications that
display the available jobs in the system tray window or may be
Electron.RTM. based applications. Agents may be a client of the
service. Agents may request to start or stop jobs and change
settings. Command line is a client of the service and is a console
application that can request to start jobs and waits for their
output. Splitting robot components can help developers, support
users, and enable computing systems to more easily run, identify,
and track what each robot component is executing. For example,
special behaviors may be configured per robot component, such as
setting up different firewall rules for the executor and the
service. As a further example, an executor may be aware of DPI
settings per monitor in some embodiments and, as a result,
workflows may be executed at any DPI regardless of the
configuration of the computing system on which they were
created.
[0027] FIG. 2 shows an RPA system 200, in accordance with one or
more embodiments. RPA system 200 may be, or may be part of, RPA
system 100 of FIG. 1. It should be noted that the "client side",
the "server side", or both, may include any desired number of
computing systems without deviating from the scope of the
invention.
[0028] As shown on the client side in this embodiment, computing
system 202 includes one or more executors 204, agent 206, and
designer 208. In other embodiments, designer 208 may not be running
on the same computing system 202. An executor 204 (which may be a
robot component as described above) runs a process and, in some
embodiments, multiple business processes may run simultaneously. In
this example, agent 206 (e.g., a Windows.RTM. service) is the
single point of contact for managing executors 204.
[0029] In some embodiments, a robot represents an association
between a machine name and a username. A robot may manage multiple
executors at the same time. On computing systems that support
multiple interactive sessions running simultaneously (e.g.,
Windows.RTM. Server 2012), multiple robots may be running at the
same time (e.g., a high density (HD) environment), each in a
separate Windows.RTM. session using a unique username.
[0030] Agent 206 is also responsible for sending the status of the
robot (e.g., periodically sending a "heartbeat" message indicating
that the robot is still functioning) and downloading the required
version of the package to be executed. The communication between
agent 206 and conductor 212 is initiated by agent 206 in some
embodiments. In the example of a notification scenario, agent 206
may open a WebSocket channel that is later used by conductor 212 to
send commands to the robot (e.g., start, stop, etc.).
[0031] As shown on the server side in this embodiment, a
presentation layer comprises web application 214, Open Data
Protocol (OData) Representative State Transfer (REST) Application
Programming Interface (API) endpoints 216 and notification and
monitoring API 218. A service layer on the server side includes API
implementation/business logic 220. A persistence layer on the
server side includes database server 222 and indexer server 224.
Conductor 212 includes web application 214, OData REST API
endpoints 216, notification and monitoring API 218, and API
implementation/business logic 220.
[0032] In various embodiments, most actions that a user performs in
the interface of conductor 212 (e.g., via browser 210) are
performed by calling various APIs. Such actions may include, but
are not limited to, starting jobs on robots, adding/removing data
in queues, scheduling jobs to run unattended, and so on. Web
application 214 is the visual layer of the server platform. In this
embodiment, web application 214 uses Hypertext Markup Language
(HTML) and JavaScript (JS). However, any desired markup languages,
script languages, or any other formats may be used without
deviating from the scope of the invention. The user interacts with
web pages from web application 214 via browser 210 in this
embodiment in order to perform various actions to control conductor
212. For instance, the user may create robot groups, assign
packages to the robots, analyze logs per robot and/or per process,
start and stop robots, etc.
[0033] In addition to web application 214, conductor 212 also
includes a service layer that exposes OData REST API endpoints 216
(or other endpoints may be implemented without deviating from the
scope of the invention). The REST API is consumed by both web
application 214 and agent 206. Agent 206 is the supervisor of one
or more robots on the client computer in this exemplary
configuration.
[0034] The REST API in this embodiment covers configuration,
logging, monitoring, and queueing functionality. The configuration
REST endpoints may be used to define and configure application
users, permissions, robots, assets, releases, and environments in
some embodiments. Logging REST endpoints may be useful for logging
different information, such as errors, explicit messages sent by
the robots, and other environment-specific information, for
example. Deployment REST endpoints may be used by the robots to
query the package version that should be executed if the start job
command is used in conductor 212. Queueing REST endpoints may be
responsible for queues and queue item management, such as adding
data to a queue, obtaining a transaction from the queue, setting
the status of a transaction, etc. Monitoring REST endpoints monitor
web application 214 and agent 206. Notification and monitoring API
218 may be REST endpoints that are used for registering agent 206,
delivering configuration settings to agent 206, and for
sending/receiving notifications from the server and agent 206.
Notification and monitoring API 218 may also use WebSocket
communication in some embodiments.
[0035] The persistence layer on the server side includes a pair of
servers in this illustrative embodiment--database server 222 (e.g.,
a SQL server) and indexer server 224. Database server 222 in this
embodiment stores the configurations of the robots, robot groups,
associated processes, users, roles, schedules, etc. This
information is managed through web application 214 in some
embodiments. Database server 222 may also manage queues and queue
items. In some embodiments, database server 222 may store messages
logged by the robots (in addition to or in lieu of indexer server
224). Indexer server 224, which is optional in some embodiments,
stores and indexes the information logged by the robots. In certain
embodiments, indexer server 224 may be disabled through
configuration settings. In some embodiments, indexer server 224
uses ElasticSearch.RTM., which is an open source project full-text
search engine. Messages logged by robots (e.g., using activities
like log message or write line) may be sent through the logging
REST endpoint(s) to indexer server 224, where they are indexed for
future utilization.
[0036] FIG. 3 is an architectural diagram illustrating a simplified
deployment example of RPA system 300, in accordance with one or
more embodiments. In some embodiments, RPA system 300 may be, or
may include RPA systems 100 and/or 200 of FIGS. 1 and 2,
respective. RPA system 300 includes multiple client computing
systems 302 running robots. Computing systems 302 are able to
communicate with a conductor computing system 304 via a web
application running thereon. Conductor computing system 304, in
turn, communicates with database server 306 and an optional indexer
server 308. With respect to FIGS. 2 and 3, it should be noted that
while a web application is used in these embodiments, any suitable
client/server software may be used without deviating from the scope
of the invention. For instance, the conductor may run a server-side
application that communicates with non-web-based client software
applications on the client computing systems.
[0037] In one embodiment, RPA system 300 may be implemented for
cloud-based management of RPA robots. Such cloud-based management
of RPA robots enables RPA to be provided as Software as a Service
(SaaS). Accordingly, conductor 304 is implemented in the cloud for
cloud-based management of RPA robots to, e.g., create RPA robots,
provision RPA robots, schedule tasks on RPA robots, decommission
RPA robots, or effectuate any other orchestration task for managing
RPA robots.
[0038] FIG. 4 shows a network architecture 400 for implementing
cloud-based management of RPA robots, in accordance with one or
more embodiments. Network architecture 400 comprises a cloud
computing environment 402 and a local computing environment 404.
Local computing environment 404 represents a local network
architecture of a user or any other entity or entities, such as,
e.g., a company, a corporation, etc. Local computing environment
404 comprises local network 406. Cloud computing environment 402
represents a cloud computing network architecture that provides
services or processing of workloads remote from the user at local
computing environment 404. Cloud computing environment 402
comprises various cloud networks, including internet 414, user
cloud network 418 representing a cloud network managed (or
controlled) by the user and hosted by a cloud platform provider,
and a cloud service provider cloud network 420 representing a cloud
network managed by a cloud service provider and hosted by a cloud
platform provider. The cloud service provider is an entity that
provides services (e.g., RPA) via the cloud. The cloud platform
provider is an entity that maintains cloud computing
infrastructure. Local network 406 of local computing environment
404 is communicatively coupled to internet 414 of cloud computing
environment 402 to facilitate communication between local computing
environment 404 and cloud computing environment 402.
[0039] As shown in FIG. 4, a cloud orchestrator 430 is implemented
in cloud computing environment 402 to enable cloud-based management
of RPA robots. In particular, cloud orchestrator 430 is managed by
a cloud service provider and hosted in cloud service provider cloud
network 420 within cloud computing environment 402. In one
embodiment, the cloud service provider provides RPA to the user in
local computing environment 404.
[0040] Cloud orchestrator 430 manages RPA robots in cloud computing
environment 402. In particular, the user interacts with computing
device 412 in local computing environment 404 to transmit
instructions for managing RPA robots to cloud orchestrator 430 in
cloud computing environment 402. Alternatively, the user interacts
with computing device 412 in local computing environment 404 to set
a schedule on cloud orchestrator 430 to automatically transmit
instructions on behalf of the user for managing RPA robots.
Exemplary instructions for managing RPA robots include instructions
for creating RPA robots, provisioning RPA robots, scheduling a task
on RPA robots (e.g., schedule a time for performing the task and a
type of robot to perform the task), decommissioning RPA robots, or
any other orchestration instructions for RPA robots. In response to
receiving the instructions, cloud orchestrator 430 effectuates the
instructions by, e.g., creating the RPA robots, provisioning the
RPA robots, scheduling the task of the RPA robot, decommissioning
the RPA robots, etc. In one embodiment, cloud orchestrator 430 also
facilitates secure access control and manages robot licenses. In
one embodiment, cloud orchestrator 430 may be similar to conductor
104 of FIG. 1, conductor 212 of FIG. 2, or conductor 304 of FIG. 3,
but implemented in cloud service provider cloud network 420 within
cloud computing environment 402.
[0041] In one embodiment, the instruction for managing RPA robots
transmitted to cloud orchestrator 430 is included in a command for
executing a job for performing an RPA workflow. In this embodiment,
cloud orchestrator 430 effectuates the instructions in response to
receiving the command for executing the job.
[0042] The RPA robots managed by cloud orchestrator 430 may include
a pool of cloud robots that are deployed and maintained within
cloud computing environment 402. Such cloud robots may include one
or more cloud service robots 428-A, . . . , 428-X (hereinafter
collectively referred to as cloud service robots 428) of cloud
service robot pool 426 and one or more cloud managed robots 424-A,
. . . , 424-Y (hereinafter collectively referred to as cloud
managed robots 424) of cloud managed robot pool 422. Such cloud
robots perform (i.e., process) tasks in cloud computing environment
402 and transmit results of the tasks to the user in local
computing environment 404. Additionally or alternatively, the RPA
robots managed by cloud orchestrator 430 may include one or more
local robots 410-A, . . . , 410-Z (hereinafter collectively
referred to as local robots 410) of local robot pool 408.
[0043] Cloud service robots 428 are maintained by the cloud service
provider in cloud service provider cloud network 420 for performing
RPA tasks in cloud computing environment 402 for the user in local
network environment 404. Cloud service robots 428 are created upon
request by the user sending instructions from computing device 412
to cloud orchestrator 430. Upon creation, cloud service robots 428
enter into a standby mode while waiting to perform a task (or
workflow). While in standby mode, the cost for running the cloud
service robots 428 is minimized or otherwise reduced. Tasks are
scheduled on cloud service robots 428 by the user sending
instructions from computing device 412 to cloud orchestrator 430.
The instructions for scheduling tasks define the time for
performing the task and a type of robot for performing the task.
Cloud service robots 428 wake up from standby mode to perform the
task and return to standby mode once the task is complete.
Accordingly, cloud service robots 428 perform the tasks on cloud
service provider cloud network 420 for the user in local computing
environment 404.
[0044] Cloud service robot pool 426 is maintained by the cloud
service provider in cloud service provider cloud network 420 to
include cloud service robots of different types. For example, cloud
service robot pool 426 may include standard robots or custom
robots. Standard robots are defined by the user using standard
machine templates, which provide a standard predetermined set of
software to the robots. Standard robots may be, e.g., machines with
only a standard browser used for web automation, machines with an
operating system installed for performing virtual desktop
infrastructure (VDI) automation, machines with standard
applications for performing desktop automation, or a combination
thereof. Custom robots are defined by the user using custom machine
templates, which provide a custom set of software to the robots.
The custom machine templates may be uploaded by the user as a
machine image for the cloud service provider to use when creating
the custom robots, or may be selected from one or more snapshot
images of virtual machines previously configured by the user.
Custom machine images may include proprietary software that is
owned by the user or special-licensed applications that were
purchased by the user. Standard and custom robots are used to run
automations (processes) that were submitted to cloud orchestrator
430. Cloud orchestrator 430 awaits instructions to execute
automations from either: a) the user directly through manual
invocation, or b) through previously scheduled regular automations.
Once cloud orchestrator 430 is ready to execute an automation, it
inspects the type of process and identifies whether it needs a
standard robot or a custom robot to execute that automation. Once
the robot type is identified, cloud orchestrator 430 inspects robot
pools available for that robot type to find an available robot that
is already running or an available robot that is almost finished
with a job. If a robot of that type is already running, cloud
orchestrator 430 will utilize that robot to avoid starting a new
robot unnecessarily in an effort to minimize costs. If no robots
are running, it will start a robot that is on standby and submit
the job request to that robot.
[0045] In one embodiment, algorithms may be applied to maximize the
utilization of the robots in cloud service robot pool 426 and to
reduce operating costs for the user. Cloud orchestrator 430 will
look ahead at the upcoming planned schedule of automation and
optimize a plan for how to parallelize and queue automations so
that they run on the minimum number of robots. Once the schedule is
defined, cloud orchestrator 430 will use the schedule to run
automations. Additionally, cloud orchestrator 430 will be
constantly monitoring the state of running robots and modify the
planned schedule based on real-measured execution of the robots.
This results in maximizing the utilization of the running robots
and reducing the costs of running additional robots.
[0046] In one embodiment, cloud service robot pool 426 may service
multiple users in a multi-tenant environment.
[0047] Cloud managed robots 424 are maintained by the user in a
user cloud network 418 for performing RPA tasks in cloud computing
environment 402 for the user in local network environment 404.
Cloud managed robots 424 are similar in capability to cloud service
robots 428 and are also hosted in cloud computing environment 402.
However, user cloud network 418, upon which cloud managed robots
424 are hosted, is managed by the user while cloud service provider
cloud network 420, upon which cloud service robots 428 are hosted,
is managed by the cloud service provider and hosted by the cloud
platform provider. Cloud orchestrator 430 manages cloud managed
robots 424 by establishing a connection between cloud service
provider cloud network 420 and user cloud network 418. User cloud
network 418 may be established by the user utilizing cloud provider
technology to tunnel back to local network 406. The user can
establish a dedicated network connection from local network 406 to
cloud service provider cloud network 420. Connectivity is typically
in the form of, e.g., an any-to-any (e.g., internet protocol
virtual private network) network, a point-to-point Ethernet
network, or a virtual cross-connection through a connectivity
provider at a co-location facility. These connections do not go
over the public Internet. This offers more reliability, faster
speeds, consistent latencies, and higher security than typical
connections over the Internet. User cloud network 418 continues to
be fully controlled and managed by the user, thereby providing
stringent control over data to the user.
[0048] Once the connection between cloud service provider cloud
network 420 and user cloud network 418 has been established, cloud
managed robots 424 are created upon request by the user interacting
with cloud orchestrator 430 via computing device 412. Cloud managed
robots 424 are created on user cloud network 418. Accordingly,
cloud managed robots 424 perform the tasks on user cloud network
418 for the user in local computing environment 404. Algorithms may
be applied to maximize the utilization of the robots in cloud
managed robot pool 422 and to reduce operating costs for the
user.
[0049] In one embodiment, cloud robots (e.g., cloud service robots
428 or cloud managed robots 424) may be created disconnected from
cloud orchestrator 430. In this embodiment, virtual machines on
which the cloud robots are implemented are created with the ability
to accept job automatically disabled, for example, by automatically
setting the accept jobs property of the virtual machines to false.
Advantageously, the virtual machines may be configured upon
creation without having jobs run on the virtual machine before they
are ready. Once the virtual machines are configured (or otherwise
ready to accept jobs), the virtual machines may be set to accept
jobs, for example, by setting the accept jobs property to true. If
needed, the accept jobs property may be set to false for
maintenance.
[0050] In one embodiment, to generate a snapshot image of a virtual
machine (e.g., executing cloud service robots 428 or cloud managed
robots 424), the virtual machine is initially implemented using a
standard machine template. The user configures the virtual machine
(e.g., via remote desktop protocol) to, for example, install and
configure a VPN (virtual private network) (e.g., VPN client or a
site-to-site VPN) to allow cloud robots executing on the virtual
machine to access assets behind the firewall of local network 406.
Once configured, a snapshot image of the configured virtual machine
is generated by the user interacting with cloud orchestrator
430.
[0051] FIG. 7 shows a user interface 700 of a cloud orchestrator
(e.g., cloud orchestrator 430 of FIG. 4), in accordance with one or
more embodiments. User interface 700 shows three virtual machines:
machine 1, machine 2, and machine 3. To generate a snapshot image
of machine 2, the user interacts with user interface 700 to stop
execution of machine 2, disable accepting of jobs by machine 2, and
selects create snapshot field 702. In response, a dialog box will
prompt the user to define various properties of the generated
snapshot image.
[0052] FIG. 8 shows a dialog box 800 for defining properties of a
generated snapshot image, in accordance with one or more
embodiments. Dialog box 800 prompts the user to define properties
such as, e.g., image name, description, and default username on
image in fields 802-806 respectively. The user may also check box
808 to set the generated snapshot image as the default image for
the robot pool. By checking box 808, all virtual machines created
in that robot pool will be created using the generated snapshot
image. Once all properties are defined, the user selects the create
box 810 to generate the snapshot image of the virtual machine. In
one embodiment, the number of snapshot images of virtual machines
may be limited to a maximum predefined number of snapshot images
(e.g., 20) to encourage maintenance. The generated snapshot image
may be used to implement new virtual machines in the cloud
orchestrator (e.g., cloud orchestrator 430). Advantageously, by
generating a snapshot image of a virtual machine for implementing
new virtual machines, there is no need for the user to create a
custom image in the user's own infrastructure and upload that image
to implement the new virtual machines.
[0053] Referring back to FIG. 4, in one embodiment, virtual
machines (including cloud robots (e.g., cloud service robots 428 or
cloud managed robots 424) on which they are executing) are manually
configured (e.g., by the user via computing device 412) via RDP
(remote desktop protocol). Cloud robots are implemented on various
virtual machines. The user may interact with cloud orchestrator 430
to enable RDP functionality for one or more of the virtual
machines. FIG. 9 shows a user interface 900 of a cloud orchestrator
(e.g., cloud orchestrator 430 of FIG. 4), in accordance with one or
more embodiments. To enable RDP functionality for Machine 2, for
example, the user interacts with user interface 900 to select
enable remote desktop field 902. In one embodiment, the RDP
functionality is disabled by default. When enabled by the user, the
RDP functionality is enabled for a predefined period of time (e.g.,
24 hours), after which the RDP functionality is automatically
disabled. In response to enabling RDP functionality, the RDP port
on the one or more virtual machines is opened. For example, the
user may remote desktop into the one or more virtual machines via
RDP to install custom software (e.g., a VPN such as a VPN client or
a site-to-site VPN) or apply any other customization. RDP
functionality will be automatically disabled after a predefined
time out period (e.g., 30 minutes), when the status of the virtual
machine is anything other than running (e.g., stopped), or when
disabled by the user interacting with cloud orchestrator 430.
Disabling RDP functionality may fail if a job is running or queued
on the cloud robot implemented on that virtual machine.
Advantageously, instead of having to grant network access for cloud
robots to local network 406, RDP enables the user to directly
configure and customize the virtual machines implementing the cloud
robots.
[0054] In one embodiment, to enable the user (e.g., via computing
device 412) to automatically push updates to manually maintained
virtual machines (e.g., executing cloud service robots 428 or cloud
managed robots 424), a maintenance window is defined. During the
maintenance window, cloud robots are automatically configured to
not accept jobs (e.g., by setting the accept jobs property to
false) and left on (or turned on if previously turned off) for the
duration of the maintenance window for applying the update. The
maintenance window may be defined according to any recurrence
pattern (e.g., weekly, monthly, etc. at a specified day and time).
Once the maintenance window ends (or once all cloud robots are
updated), the cloud robots are automatically configured to accept
jobs (e.g., by setting the accept jobs property to true).
Advantageously, the maintenance window enables automatic software
updates to be installed on the virtual machines in a manner that
does not cause RPA jobs to fail (e.g., if an application is being
updated and an RPA job tries to interact with it, the RPA job would
fail).
[0055] In one embodiment, the maintenance window may be configured
for rolling updates. In this embodiment, cloud robots are separated
into portions and cloud robots are updated portion-by-portion
during the maintenance window such that cloud robots of portions
that are not being updated continue to accept jobs. In one example,
cloud robots may be separated in half. During a first period of
time of the maintenance window, the first half of the cloud robots
are taken offline (e.g., by setting accept jobs to false) and
updated while the second half of the cloud robots continue to
accept jobs. Once the first half of the cloud robots are updated,
during a second period of time of the maintenance window, the first
half of the cloud robots are returned online to accept jobs and the
second portion of the cloud robots are taken offline and updated.
The cloud robots may be selected to be in the first portion or
second portion based on, for example, whether the robot is running
a job such that an idle robot is selected first before a robot
running a job. If there are an odd number of cloud robots, the
number of cloud robots will be rounded up and the first portion or
second portion may have an extra robot.
[0056] In one embodiment, cloud managed robot pool 422 and/or cloud
service robot pool 426 may be automatic machine pools where virtual
machines are created or deleted to automatically scale the cloud
robots as needed based on the workload. The virtual machines of the
automatic machine pools may be implemented using standard machine
templates or custom machine templates. In one embodiment, the
virtual machines of the automatic machine pools are implements
using generated snapshot images of virtual machines configured with
a VPN (e.g., a VPN client or a site-to-site VPN) to access data
behind the firewall of local network 406.
[0057] In one embodiment, cloud service robots 428 of cloud service
robot pool 426 may be licensed from the cloud service provider
based on a model of robot units. The user purchases bundles of
robot units and uses the robot units license one or more cloud
service robots 428 according to a deployment model. The deployment
model may comprise, for example, a reserved instance model or a pay
by day model. In the reserved instance model, the user commits to
using a robot for a predetermined period of time (e.g., 1 month) in
exchange for a relatively lower cost. In the pay by day model,
robots are licensed per day (or any other predetermined period of
time) in exchange for a relatively higher cost. The robot units may
be utilized for licensing other types of RPA robots (e.g.,
serverless robots).
[0058] Local robots 410 are maintained by the user in local network
406 for performing RPA tasks for the user in local network
environment 404. Local network 406 is controlled or otherwise
managed by the user. Cloud Orchestrator 430 maintains a connection
to local robots 410 through standard HTTPS connectivity. Local
robots 410 are configured using a secure network key that the user
extracts from the user interface of cloud orchestrator 430. Using
that secure key, local robots 410 reach out to cloud orchestrator
430 and establish a secure connection. All traffic happens as
outbound requests from the local robots 410. This minimizes the
need for inbound connectivity from the cloud to local network 406
which improves security.
[0059] FIG. 5 shows a method 500 for cloud-based management of RPA
robots, in accordance with one or more embodiments. Method 500 will
be described with continued reference to network architecture 400
of FIG. 4. In one embodiment, the steps of method 500 are performed
by cloud orchestrator 430.
[0060] At step 502, an instruction for managing an RPA robot is
received at an orchestrator 430 in a cloud computing environment
402 from a user in a local computing environment 404. The
instruction for managing the RPA robot may include, for example, an
instruction for creating the RPA robot, provisioning the RPA robot,
scheduling a task on the RPA robot, and/or decommissioning the RPA
robot. The RPA robot may include local robots 410, cloud managed
robots 424, or cloud service robots 428. The cloud managed robots
424 and cloud service robots 428 are for performing RPA tasks in
the cloud computing environment and transmitting results of the RPA
tasks to the user in the local computing environment 404. While not
performing a task, the RPA robots are in a standby mode having
reduced operating costs.
[0061] At step 504, in response to receiving the instruction, the
instruction for managing the RPA robot is effectuated. In one
embodiment, where the instruction for managing the RPA robot is an
instruction for creating the RPA robot, the instruction is
effectuated by creating the RPA robot for execution in a cloud
network 418 managed by the user in the cloud computing environment
402, by creating the RPA robot for execution in a cloud network 420
managed by a cloud service provider (associated with the cloud
orchestrator 430) in the cloud computing environment 402, or by
creating the RPA robot for execution in a local network 406 managed
by the user in the local computing environment 404.
[0062] In one embodiment, the instruction for managing the RPA
robot received by orchestrator 430 at step 502 is included in a
command for executing a job for performing an RPA workflow and the
command for executing the job is received at orchestrator 430. The
instruction for managing the RPA robot is then effectuated by
orchestrator 430 in response to receiving the command for executing
the job.
[0063] Advantageously, embodiments of the present invention enable
RPA as a SaaS. Such SaaS RPA enables users to create and scale the
number of robots on demand for automating tasks using the cloud,
for example, during a time period of peak usage. Such SaaS RPA
lowers the total cost of ownership for the user by reducing cloud
operating costs, simplifies the network infrastructure required to
implement RPA, and enables a secure cloud-based infrastructure for
implementing RPA.
[0064] One illustrative application of embodiments of the present
invention will be described with reference to FIG. 4. An airline
company may utilize RPA robots for customer service to modify
airline bookings. The airline company provisions ten RPA robots as
local robots 410 on a local computing environment 404, which is
sufficient for handling customer service at a regular load.
Occasionally, the airline company will have an emergency, such as,
e.g., a thunderstorm at one of their hubs that may require
grounding a few hundred airplanes within a time period of a few
hours, resulting in tens of thousands of customers stranded at
airports and attempting to reschedule their flights. Customer
service representatives at the airport and the ten RPA robots are
unable to handle this additional load. Advantageously, embodiments
of the present invention enable the airline company to scale up the
number of RPA robots to a few hundred RPA robots as cloud service
robots 428 to help serve the stranded customers immediately. The
airline company is able to scale the number of RPA robots without
having to manage the infrastructure for the additional RPA robots
or having to provision the RPA robots for peak capacity during
normal operation times. Further, the airline company would only pay
for the additional RPA robots during peak usage, thereby reducing
costs.
[0065] FIG. 6 is a block diagram illustrating a computing system
600 configured to execute the methods described in reference to
FIG. 5, according to an embodiment of the present invention. In
some embodiments, computing system 600 may be one or more of the
computing systems depicted and/or described herein, such as, e.g.,
conductor 104, robots 106, unattended robot 110, and attended robot
108 of FIG. 1, conductor 212 of FIG. 2, robots 302 and conductor
304 of FIG. 3, and local robots 410, computing device 412, cloud
managed robots 424, cloud service robots 428, and cloud
orchestrator 430 of FIG. 4. Computing system 600 includes a bus 602
or other communication mechanism for communicating information, and
processor(s) 604 coupled to bus 602 for processing information.
Processor(s) 604 may be any type of general or specific purpose
processor, including a Central Processing Unit (CPU), an
Application Specific Integrated Circuit (ASIC), a Field
Programmable Gate Array (FPGA), a Graphics Processing Unit (GPU),
multiple instances thereof, and/or any combination thereof.
Processor(s) 604 may also have multiple processing cores, and at
least some of the cores may be configured to perform specific
functions. Multi-parallel processing may be used in some
embodiments.
[0066] Computing system 600 further includes a memory 606 for
storing information and instructions to be executed by processor(s)
604. Memory 606 can be comprised of any combination of Random
Access Memory (RAM), Read Only Memory (ROM), flash memory, cache,
static storage such as a magnetic or optical disk, or any other
types of non-transitory computer-readable media or combinations
thereof. Non-transitory computer-readable media may be any
available media that can be accessed by processor(s) 604 and may
include volatile media, non-volatile media, or both. The media may
also be removable, non-removable, or both.
[0067] Additionally, computing system 600 includes a communication
device 608, such as a transceiver, to provide access to a
communications network via a wireless and/or wired connection
according to any currently existing or future-implemented
communications standard and/or protocol.
[0068] Processor(s) 604 are further coupled via bus 602 to a
display 610 that is suitable for displaying information to a user.
Display 610 may also be configured as a touch display and/or any
suitable haptic I/O device.
[0069] A keyboard 612 and a cursor control device 614, such as a
computer mouse, a touchpad, etc., are further coupled to bus 602 to
enable a user to interface with computing system. However, in
certain embodiments, a physical keyboard and mouse may not be
present, and the user may interact with the device solely through
display 610 and/or a touchpad (not shown). Any type and combination
of input devices may be used as a matter of design choice. In
certain embodiments, no physical input device and/or display is
present. For instance, the user may interact with computing system
600 remotely via another computing system in communication
therewith, or computing system 600 may operate autonomously.
[0070] Memory 606 stores software modules that provide
functionality when executed by processor(s) 604. The modules
include an operating system 616 for computing system 600 and one or
more additional functional modules 618 configured to perform all or
part of the processes described herein or derivatives thereof.
[0071] One skilled in the art will appreciate that a "system" could
be embodied as a server, an embedded computing system, a personal
computer, a console, a personal digital assistant (PDA), a cell
phone, a tablet computing device, a quantum computing system, or
any other suitable computing device, or combination of devices
without deviating from the scope of the invention. Presenting the
above-described functions as being performed by a "system" is not
intended to limit the scope of the present invention in any way,
but is intended to provide one example of the many embodiments of
the present invention. Indeed, methods, systems, and apparatuses
disclosed herein may be implemented in localized and distributed
forms consistent with computing technology, including cloud
computing systems.
[0072] It should be noted that some of the system features
described in this specification have been presented as modules, in
order to more particularly emphasize their implementation
independence. For example, a module may be implemented as a
hardware circuit comprising custom very large scale integration
(VLSI) circuits or gate arrays, off-the-shelf semiconductors such
as logic chips, transistors, or other discrete components. A module
may also be implemented in programmable hardware devices such as
field programmable gate arrays, programmable array logic,
programmable logic devices, graphics processing units, or the like.
A module may also be at least partially implemented in software for
execution by various types of processors. An identified unit of
executable code may, for instance, include one or more physical or
logical blocks of computer instructions that may, for instance, be
organized as an object, procedure, or function. Nevertheless, the
executables of an identified module need not be physically located
together, but may include disparate instructions stored in
different locations that, when joined logically together, comprise
the module and achieve the stated purpose for the module. Further,
modules may be stored on a computer-readable medium, which may be,
for instance, a hard disk drive, flash device, RAM, tape, and/or
any other such non-transitory computer-readable medium used to
store data without deviating from the scope of the invention.
Indeed, a module of executable code could be a single instruction,
or many instructions, and may even be distributed over several
different code segments, among different programs, and across
several memory devices. Similarly, operational data may be
identified and illustrated herein within modules, and may be
embodied in any suitable form and organized within any suitable
type of data structure. The operational data may be collected as a
single data set, or may be distributed over different locations
including over different storage devices, and may exist, at least
partially, merely as electronic signals on a system or network.
[0073] The foregoing merely illustrates the principles of the
disclosure. It will thus be appreciated that those skilled in the
art will be able to devise various arrangements that, although not
explicitly described or shown herein, embody the principles of the
disclosure and are included within its spirit and scope.
Furthermore, all examples and conditional language recited herein
are principally intended to be only for pedagogical purposes to aid
the reader in understanding the principles of the disclosure and
the concepts contributed by the inventor to furthering the art, and
are to be construed as being without limitation to such
specifically recited examples and conditions. Moreover, all
statements herein reciting principles, aspects, and embodiments of
the disclosure, as well as specific examples thereof, are intended
to encompass both structural and functional equivalents thereof.
Additionally, it is intended that such equivalents include both
currently known equivalents as well as equivalents developed in the
future.
* * * * *